A machine learning device uses a machine learning model to process collected data and output a result. The machine learning device may use feedback to update or improve the machine learning model. For example, a machine learning device may use a regression analysis model to make a prediction, and may then update the regression analysis model based on feedback that indicates whether the prediction was correct. A variety of types of machine learning models exists (e.g., linear regression model, naïve Bayes classifier). Machine learning models are commonly used for addressing “Big Data” problems, where the volume of data to be processed may be great and/or real time data processing may be desired.